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Solving Scheduling Problems by Evolutionary Algorithms for Graph Coloring Problem

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Metaheuristics for Scheduling in Industrial and Manufacturing Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 128))

Summary

This chapter presents a new evolutionary approach to the Graph Coloring Problem (GCP) as a generalization of some scheduling problems: timetabling, scheduling, multiprocessor scheduling task and other assignment problems. The proposed evolutionary approach to the Graph Coloring Problem utilizes information about the conflict localization in a given coloring. In this context a partial fitness function (pff) and its usage to specialize genetic operators (IBIS and BCX) and phenotypic measure of diversity in population are described. The particular attention is given to the practical usage of GCP. The performance of the proposed algorithm is verified by computer experiments on the set of benchmark graphs instances (DIMACS). Additional experiments were done on benchmark graph for timetabling problem.

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Author information

Authors and Affiliations

  1. Institute of Applied Informatics, Wroclaw University of Technology (Poland), Poland

    Pawel B. Myszkowski

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  1. Pawel B. Myszkowski
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Editors and Affiliations

  1. Department of Languages and Informatics Systems, Polytechnic University of Catalonia, Campus Nord, Ed. Omega C/Jordi Girona 1-3, 08034, Barcelona, Spain

    Fatos Xhafa

  2. Norwegian Center of Excellence Center of Excellence for Quantifiable Quality of Service, Norwegian University of Science and Technology, O.S. Bragstads plass 2E, NO-7491, Trondheim, Norway

    Ajith Abraham

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Myszkowski, P.B. (2008). Solving Scheduling Problems by Evolutionary Algorithms for Graph Coloring Problem. In: Xhafa, F., Abraham, A. (eds) Metaheuristics for Scheduling in Industrial and Manufacturing Applications. Studies in Computational Intelligence, vol 128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78985-7_7

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  • DOI: https://doi.org/10.1007/978-3-540-78985-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78984-0

  • Online ISBN: 978-3-540-78985-7

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